拖累 发表于 2025-3-21 17:25:26
书目名称Mathematical Optimization Theory and Operations Research: Recent Trends影响因子(影响力)<br> http://impactfactor.cn/if/?ISSN=BK0626492<br><br> <br><br>书目名称Mathematical Optimization Theory and Operations Research: Recent Trends影响因子(影响力)学科排名<br> http://impactfactor.cn/ifr/?ISSN=BK0626492<br><br> <br><br>书目名称Mathematical Optimization Theory and Operations Research: Recent Trends网络公开度<br> http://impactfactor.cn/at/?ISSN=BK0626492<br><br> <br><br>书目名称Mathematical Optimization Theory and Operations Research: Recent Trends网络公开度学科排名<br> http://impactfactor.cn/atr/?ISSN=BK0626492<br><br> <br><br>书目名称Mathematical Optimization Theory and Operations Research: Recent Trends被引频次<br> http://impactfactor.cn/tc/?ISSN=BK0626492<br><br> <br><br>书目名称Mathematical Optimization Theory and Operations Research: Recent Trends被引频次学科排名<br> http://impactfactor.cn/tcr/?ISSN=BK0626492<br><br> <br><br>书目名称Mathematical Optimization Theory and Operations Research: Recent Trends年度引用<br> http://impactfactor.cn/ii/?ISSN=BK0626492<br><br> <br><br>书目名称Mathematical Optimization Theory and Operations Research: Recent Trends年度引用学科排名<br> http://impactfactor.cn/iir/?ISSN=BK0626492<br><br> <br><br>书目名称Mathematical Optimization Theory and Operations Research: Recent Trends读者反馈<br> http://impactfactor.cn/5y/?ISSN=BK0626492<br><br> <br><br>书目名称Mathematical Optimization Theory and Operations Research: Recent Trends读者反馈学科排名<br> http://impactfactor.cn/5yr/?ISSN=BK0626492<br><br> <br><br>Foment 发表于 2025-3-21 20:17:58
https://doi.org/10.1007/978-3-030-86433-0optimization; artificial intelligence; computer systems; graph theory; theoretical computer science; comp破裂 发表于 2025-3-22 02:21:08
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1865-0929MOTOR 2021, held in Irkutsk, Russia, in July 2021. Due to the COVID-19 pandemic the conference was held online. .The 31 full papers and 3 short papers presented in this volume were carefully reviewed and selected from a total of 102 submissions. The papers in the volume are organised according to微不足道 发表于 2025-3-22 23:49:35
Application of Smooth Approximation in Stochastic Optimization Problems with a Polyhedral Loss Funct and Heaviside function with sigmoid function. This replacement leads to the approximation of their gradients. Next, the problem solved using modified gradient descent. The accuracy and effectiveness of this method are shown in two examples. Also, we discuss some aspects of such approximations in the case of discrete random distribution.毁坏 发表于 2025-3-23 02:19:47
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1865-0929the following topical headings: continuous optimization; integer programming and combinatorial optimization; operational research applications; optimal control..978-3-030-86432-3978-3-030-86433-0Series ISSN 1865-0929 Series E-ISSN 1865-0937